Introduction

Human coronavirus disease, a global public health concern first described in December 2019 and caused by SARS-CoV2 or CoVID-19 manifests with varying degree of signs and symptoms [1,2]. Three major categories of patients with confirmed Covid-19 infection have been recognized: critical patients (~5% of total) requiring life sustaining treatments or procedures, having ARDS, sepsis or septic shock; severe patients (~15% of total) who show signs of pneumonia, severe respiratory distress or oxygen saturation <90%; and non-severe representing both mild and/or moderate cases (~80% of total) who show absence of severe or critical disease signs [3]. Other groups of patients who remain free of any disease during the course of Covid-19 infection called asymptomatic (~17-25%) have also been described [3]. Various factors such as surveillance strategies, therapeutic interventions employed, regional demographics, Covid-19 genotype evolution, and vaccination can be expected to alter Covid-19 severity turnover.

Covid-19 is a highly infectious disease that can lead to fatality. As of January 2023, WHO dashboard (covid19.who.int) shows the number of confirmed deaths reported due to Covid-19 to be 6.8 million globally with a case fatality rate of 0.91%. In Saudi Arabia, the number of deaths due to Covid-19 stands at 9571 (covid19.moh.gov.sa) with a case fatality rate of 1.56%. In China and other countries, a case fatality rate of 4-6% in Covid-19 has been reported [4]. Although vaccination against Covid-19 has had a substantial impact on requirement of hospitalization, disease severity, and mortality rate, uncertainties about their efficacy duration and ‘long Covid-19’ [5] do highlight the need for the identification of better markers for risk stratification, prognostication and effective treatment modalities. Laboratory and radiology-based findings [6,7] could offer an easy and routinely achievable platform to assess predictive markers of disease severity in Covid-19 infection. This study aims to evaluate the significance of laboratory-based inflammatory markers, neutrophil-lymphocyte ratio, and radiological findings among different disease severity groups of COVID-19 patients admitted to a tertiary-care King Fahad Medical City in Riyadh, Saudi Arabia. To our knowledge, this is the first comprehensive laboratory-based investigation from Saudi Arabia and we believe that retrospective analyses are currently a more feasible and practical approach to study laboratory markers in a large cohort of Covid-19 patients.

Methods

Patients

The full cohort of 412 patients included all those admitted to King Fahad Medical City during the peak of pandemic and confirmed by polymerase chain reaction on nasopharyngeal swabs to be Covid-19 positive. Diagnostic criteria and management of patients was done in accordance with WHO and the Ministry of Health, Kingdom of Saudi Arabia guidelines at that time. All the records of the patients PCR results were handled in the Central Command Centre of the Infection Control and Environmental Health department at KFMC. The Departments of PCLMA, Infection Control and KFMC IRB approved the study. Due to the secondary use of data obtained during routine clinical care without any patient contact or harm, informed consent waiver in accordance with IRB policy was obtained.

Routine serial hematologic, biochemical, immunological and/or radiologic investigations were done at KFMC laboratories (CAP accredited). All the data are stored in the hospital management system (EPIC) in individual patient files. Socio-demographic, laboratory and radiologic data were extracted from the medical records and anonymized. Patients were categorized into various disease severity groups in accordance with WHO severity criteria.

Statistical Analysis Procedure

All categorical variables such as gender, age group, nationality, outcomes and severity presented as frequencies and percentages. Continuous variables age, time (days), WBC, Neutrophil, etc. expressed as either Mean ± SD or Median [IQR] depending on the normality of data. The Kolmogorov-Smirnov test was used to confirm the assumption of normal distribution. If the data was biased, a nonparametric test was used. Pearson chi-square / Fisher’s exact test was used to determine significant associations between categorical variables, depending on whether the cell was expected to have an expected frequency of less than 5. One-way ANOVA / Kruskal-Wallis test was used to determine the mean / median significant difference between severity of COVID-19 and factors of the study variables. Overall survival of the patients determined the Kaplan-Meir analysis. A two-sided p-value less than 0.05 was considered statistically significant. All data was entered and analyzed using the SPSS 25 Statistics Package (SPSS Inc., Chicago, Illinois, USA) and MEDCALC software version 20.118.

Results

Patient socio-demographic and clinical characteristics

Table 1 shows the socio-demographic, clinical features and radiological findings of patients based on their categorization into disease severity groups: 160 critical (38.8%) all intubated, 153 severe (37.1%) and 99 moderate (24%) with a mortality of 44%, 19%, and 3%, respectively. Kaplan-Meir analysis of the Overall Survival (OS) showed highly significant lower OS in critical and severe compared with moderate patients (Figure 1a).

Figure 3: Clinical outcome (survival/death) related to laboratory markers with disease severity in Covid-19 patients: box plot showing Covid-19 related deaths (blue) and survival (greenred) with respect to different laboratory parameters. The data are extrapolated from the values at discharge or before death.

Table 4: Laboratory marker distribution in Covid-19 disease severity.

Discussion

The assessment of clinical laboratory-based diagnostic and prognostic markers that have a high predictive value on disease severity and outcome in Covid-19 patients is critical for their effective management, help prevent progression and thus, reduce mortality. We performed retrospective analyses of the sociodemographic, clinical laboratory and radiological features of 412 patients with confirmed Covid-19 infection admitted to our hospital.

We had more critical and severe (76%) than non-severe (24%) Covid-19 cases expected of the medical city in dealing with highrisk patients. In Covid-19, the progression from one severity form to the other may be sudden with even a fatal outcome. Therefore, a clear distinction of the disease severity groups is very essential for various reasons. Frist, non-severe Covid-19 patients may progress to ARDS, septic shock, or multiple organ dysfunction syndrome [8] leading to higher fatality. Second, severe or critical patients have an overall poor prognosis and therefore, their identification earlyon is crucial. Importantly, fewer laboratory studies are available that have considered disease severity and clinical outcome. We had significantly higher survival rate in non-severe (97%) followed by severe (81%) and critical patients (56%). In a cohort of 345 patients, Chen R et al. reported the fatality rate of 60% in critical, 34% in severe and 6% in non-severe patients [9]. Consideration of disease severity groups in non-human animal models of Covid-19 should also be taken into account if any similarities are to be drawn.

We had more non-Saudi (52.7%) than Saudi (47.3%) patients. This could just be a coincidence. However, one possible explanation could be that more than a third (~13.5 million) of Saudi’s population (35 million) is made up of expatriates from multiple nationalities with various ethnic and linguistic groups from other Arab countries, Asia, Europe, and America (the General Authority for Statistics). Covid-19 can occur in all age groups and age is an important risk factor for the infection. The median patient age was about 55 years with an age distribution below 30 to over 70 years. The percentage survival decreased with increasing age in critical and severe patients and majority of non-severe patients survived in all age groups. Y. Sun, et al. reported the median patient age at 47 years with mild illness in less than 30 years [10]. A meta-analysis in a total of 4663 patients revealed mean age of 48.4 years [4]. A retrospective cohort study found that older age is associated with risk of death [9,11]. Our cohort included more males with significant differences among severity groups and slightly more number of deaths in females than males. Chen R, et al. reported 67% males among all non-survivors, reaching 83% in critical patients [9].

Symptoms on admission and any associated comorbidities are important risk factors in Covid-19 patients. More than half of the critical patients with coexisting cardiac disease and diabetes mellitus did not survive (Table). Symptoms of cough, sputum, and dyspnea were found more common in severe or critical patients, and with non-survivors [9]. Symptoms such as fatigue, anosmia, dyspnea, cough, and myalgia may persist in ‘long Covid’ [12]. A study by Kompaniyets, et al. showed a higher relative risk for people with complicated diabetes, obesity, and anxiety related disorders (~1.3) and cardiovascular disease (1.1) [13]. A higher risk of adverse Covid-19 outcome that increases with age as seen in our study is estimated to be in about 20% of individuals with chronic conditions [13-15]. A study by Aleanizy FS, et al. also revealed old age, fever, and comorbidities involving diabetes mellitus, asthma, and smoking to be significantly associated with infection severity [16].

We observed higher NLR in critical and severe patients on admission, and in non-survivors compared with survivors. Although lymphopenia and neutrophilia is a prominent finding in most Covid-19 patients [6,17,18], NLR is currently considered as a good predictive marker in disease severity and mortality in Covid-19 patients [19]. Yang, et al. reported elevated NLR to predict prognosis [20]. A meta-analysis by Li X, et al. reported higher NLR of sever patients than mild patients, and also with higher predictive value on mortality [21]. Thus, NLR readily obtained from routine differential CBC analysis could in future, be used as a routine predictive marker in not only Covid-19 infection but also other infections. However, NLR threshold is not clearly defined even in studies that have reported predictive value of NLR on disease severity and mortality. With a larger patient cohort, our study could be used to set up this threshold since comparison of NLR was performed between survivors and non-survivors across all severity groups including the NLR value on admission.

Inflammatory response in all acute infections, with no exception to Covid-19 may be a result of a cytokine storm event [2]. In turn, CRP, ESR, ferritin and LDH levels are elevated as reported by others [22,23]. Abnormal levels of these inflammatory markers could reflect damaged tissues and systemic diseases such as carcinomatosis, collagen vascular disease, sepsis, anemias, thalassemia, chronic liver disease or renal disease. Thus, these markers could be valuable for physicians in assessing these conditions when dealing with Covid-19 patients. Association of these laboratory markers with poor clinical outcome in critical and sever Covdi-19 patients suggests their high predictive value in the se severity groups.

Coagulopathy in terms of Disseminated Intravascular Coagulation (DIC) was reported in Covid-19 patients who died compared with those who survived [24]. We recently reported a CVST case of critical Covid-19 with high Ddimer, who successfully was discharged with preemptive treatment modality. Others have also reported elevated Ddimer in severe than nonsever patients contributing to an array of events with unfavorable clinical outcome.

Increased liver enzyme and cardiac marker levels in critical and sever patients indicates liver or cardiac-related complications in Covid-19. Viral infection of the bile duct cells or antiviral drug induced liver damage is common in COVID-19 patients [25]. Among patients with COVID-19, there is a high prevalence of cardiovascular disease, and >7% of patients experience myocardial injury from the infection (22% of critically ill patients). Although COVID-19 interacts with the cardiovascular system on multiple levels, increasing morbidity in patients with underlying cardiovascular conditions and provoking myocardial injury and dysfunction [26].

In conclusion, the patients with Covid-19 can experience a range of clinical manifestations with different severity spectrum that may change with age and time. Differential Clinical laboratory marker profiles between survivors and non-survivors in Covid-19 patients with variable severity are observed. The assessment of clinical laboratory-based diagnostic and prognostic markers may provide a simple, rapid, and readily available means of predicting and preventing Covid-19 disease progression, thereby help reduce mortality.

Acknowledgement

We thank KFMC Research Center, Faculty of Medicine for their support. King Fahad Medical City Institutional Review Board (IRB-20-498) approved this study.

Authorship List

SM and HS are physicians in Pulmonary Medicine dealing with patients, collected data, and performed clinical characterization of patients.

MSB is a Biostatistician at KFMC Research Center who performed statistical analysis.

AW and FA are physicians who managed and recorded all Covid-19 related cases.

MS and MN are laboratory consultants managing all laboratory data, involved in manuscript editing.

AAPZ collected data, designed the study and wrote the manuscript.

Conflict of Interest: The authors declare that there is no conflict of interest regarding the publication of this article.

Meeting where data presented (Oral): November 26-Nov 28, 2022: UK-ICN Focused workshop: International Conference on Severe Coronavirus Infection, King Fahad Medical City, Saudi Arabia.

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